librosa | Python library for audio and music analysis | Audio Utils library
kandi X-RAY | librosa Summary
kandi X-RAY | librosa Summary
Python library for audio and music analysis
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Top functions reviewed by kandi - BETA
- Reassign a spectrum
- R Frequency Fourier Transform
- Convert frames to samples
- Convert frames to time
- R Discrete Discretization
- Backtracking algorithm
- Fill off off the diagonal
- Calculates the cost for each step
- Compute a hybrid CQT
- Create an audio stream from a sound file
- Convenience function to format data
- Calculate the probability density distribution for a given time series
- Spectral Time series
- Cross similarity between two arrays
- Draw waveshow
- Compute the beat track
- Convenience function for creating MFCCs
- R Adds a path - wise path - wise path
- Create a filter with constant q values
- Spectral TimeSeries
- Compute the spectral contrast
- Calculate a griffin - lim
- Plot the spectrum
- Normalize a vector
- Hyperparameters
- Convenience function for PCEN
librosa Key Features
librosa Examples and Code Snippets
Lines of Code : 122License : Non-SPDX (ISC License)
Copy# coding: utf-8
"""
======================
Using display.specshow
======================
This notebook gives a more in-depth demonstration of all things that `specshow`
can do to help generate beautiful visualizations of spectro-temporal data.
"""
# -*- coding: utf-8 -*-
"""
======================
Laplacian segmentation
======================
This notebook implements the laplacian segmentation method of
`McFee and Ellis, 2014 `_,
with a couple of minor stability improvements.
Throughout the # coding: utf-8
"""
===================================
Enhanced chroma and chroma variants
===================================
This notebook demonstrates a variety of techniques for enhancing chroma features and
also, introduces chroma variants im python3 -m pip install numpy
plt.savefig(os.path.join(out_dir,folder,'chroma{:04}.jpg'.format(i)))
for folder in os.listdir(data_dir):
i=0
for fil in os.listdir(os.path.join(data_dir,folder)):
dir=os.path.join(data_dir,folder,fil)
with soundfile.SoundFile(dir) as audio:
waveform=audio.read(dtype="float32")
samplefor i in os.listdir(wav_path)
for i, path in enumerate(os.listdir(wav_path))
ax1.plot(np.linspace(0, sample_rate/len(samples), len(samples)), samples)
from pathlib import Path
from glob import glob
from copy_sph_to_wav import copy_sph_to_wav
from copy_wav_to_wav import copy_wav_to_wav
STAGE = "/media/catskills/interspeech22"
CHALLENGE = "openasr21"
LANGUAGE = "farsi"
SAMPLE_RATE = 16000rule all:
input:
expand("{your_path}.extension", replacements)
rule make_output:
input: "{input}_{num}.extension"
output: "{output}_{num}.extension"
shell:
copy_sph_to_wav {input} > {output}
Community Discussions
Trending Discussions on librosa
QUESTION
I am running a simple CNN using Pytorch for some audio classification on my Raspberry Pi 4 on Python 3.9.2 (64-bit). For the audio manipulation needed I am using librosa. librosa depends on the numba package which is only compatible with numpy version <= 1.20.
When running my code, the line
...ANSWER
Answered 2022-Mar-31 at 08:17Have you installed numpy using pip?
QUESTION
I'm doing test_split before the feature extraction. however, when I try to loop through any set, whether train or test, I get the following error (ValueError: too many values to unpack(expected 2))
...ANSWER
Answered 2022-Mar-15 at 13:05You should use zip to group the variables in a python iterator:
QUESTION
I want to make a rule which for a given number of threads translates files in one directory and format to another directory and format, in parallel. Certain elements of the path are defined by variables and certain are wildcards. I want it to wildcard on phase and sample and ext but take stage, challenge and language from the Python variable environment. I want the copy operation to take file to file. I don't want it to get the entire list of files as input. I'm not using expand here because if I use expand then snakemake will pass the entire list of inputs as {input} and the entire list of outputs as {output} to the function, which is not what I want. Here is the Snakefile:
ANSWER
Answered 2022-Feb-12 at 23:55Try this:
QUESTION
My application works properly on the local machine. However, as I uploaded the application to elastic beanstalk, the import of librosa library broke the application. How to solve the issue?
...ANSWER
Answered 2022-Feb-12 at 23:21The issue is probably with tensorflow==2.2.0. This is a very heavy library and you can't install it on t2.micro. You need at least t2.medium (not in free tier) which has more RAM to successfully install tensorflow==2.2.0 on EB.
QUESTION
I'm looking to write a function that takes an audio signal (assuming it contains a single instrument playing), out of which I would like to extract the instrument-like features out of the audio and into a vector space. So in theory, if I had two signals with similar-sounding instruments (such as two pianos), their respective vectors should be fairly similar (by euclidian distance/cosine similarity/etc.). How would one go about doing this?
What I've tried: I'm currently extracting (and temporally averaging) the chroma energy, spectral contrast, MFCC (and their 1st and 2nd derivatives), as well as the Mel spectrogram and concatenating them into a single representation vector:
...ANSWER
Answered 2022-Jan-24 at 23:21The part of the instrument audio that gives its distinctive sound, independently from the pitch played, is called the timbre. The modern approach to get a vector representation, would be to train a neural network. This kind of learned vector representation is often called to create an audio embedding.
An example implementation of this is described in Learning Disentangled Representations Of Timbre And Pitch For Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders (2019).
QUESTION
hi guys I'm trying to do audio classification using python and I installed a package and when I tried to use the functions, it said "TypeError: TypeError: reduce_noise() got an unexpected keyword argument 'audio_clip' hear the code of function.
import librosa import numpy as np import noisereduce as nr
def save_STFT(file, name, activity, subject): #read audio data audio_data, sample_rate = librosa.load(file) print(file)
...ANSWER
Answered 2021-Sep-23 at 14:48Answer to your question is in the error message.
QUESTION
Hi i'm trying to get a custom spectrogram layer going and I can't
...ANSWER
Answered 2021-Dec-02 at 14:57TensorFlow can't compute the output shape of your layer. As Conv2D requires a specific shape (4 dimensions), it will fail if the output shape of the previous layer is not known (None).
To fix that, you need to specify which axis you want to squeeze in you call function.
Here, I specify that this is the last axis that need to be squeezed (the channel axis).
QUESTION
I was trying to run a WaveNet, which is specified in https://github.com/mjpyeon/wavenet-classifier/blob/master/WaveNetClassifier.py.
Part of my code is as follows:
...ANSWER
Answered 2021-Nov-18 at 09:07Your data is a missing dimension. A Conv1D layer requires the input shape (timesteps, features). You seem to only have the timesteps or features. So maybe try something like this:
QUESTION
I am training a neural network and would like to check its accuracy. I've used Librosa and SciKitLearn to represent audio in the form of 1D Numpy arrays. Thus x_train, x_test, y_train, and y_test are all 1D Numpy arrays with the x_* arrays containing floats and the y_* arrays containing strings corresponding to classes of data. For example:
ANSWER
Answered 2021-Oct-24 at 18:24The predicted variable contains both values and indices, you need to do pred_vals, pred_inds = torch.max(outputs.data, 1) and then you can do correct_train += (sum(pred_inds == label)).item()
Also you don't need to convert to float before summing, you can use:
(predicted == label).sum().item()
(predicted == label) returns a BoolTensor which can be summed to obtain a float value.
QUESTION
I am trying to deploy a flask application that uses TensorFlow and Librosa. So as a dependency of Librosa I need the sndfile package.
When I run my Flask app I get this error:
...ANSWER
Answered 2021-Sep-28 at 01:22You need to install libsndfile and it's development files. Unfortunately it's not packaged up in a repository, but you can get it installed by downloading the RPMs directly
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